My career goal is to become an independent and established researcher in molecular epidemiology with expertise in viral and inflammatory factors related to cancer etiology and prevention. This goal builds upon my previous training in epidemiologic methods and virology, but requires further training in immunology and biostatistics. At the end of this training period, I will have the expertise and preliminary data to submit for funding of my independent research in cancer epidemiology and prevention. I have developed a comprehensive education and mentoring plan. My education plan will provide intensive instruction in the areas of immunology, and biostatistical methods for molecular epidemiology. I have chosen four mentors who will supervise specific portions of my training and research. Dr. Melissa Bondy will mentor me in molecular and genetic epidemiology and cancer prevention and will guide my career development; Dr. Thomas Albrecht provide guidance in immunology and virology; Dr. Charles Cobbs will provide expertise in brain anatomy, physiology, and neuro-oncology; and Dr. Kim-Ann Do will supervise the development and application of biostatistical methods, especially as they related to the use of microarrays in epidemiologic research. My research proposal will focus on examining viral and immunologic factors in glioma risk and patient outcome. I propose to capitalize on the availability of epidemiologic and genetic marker data and clinical specimens from an existing case-control study (R01CA070917) under the direction of Dr. Melissa Bondy. This study currently includes over 1200, mostly Caucasian, glioma cases and controls, matched on sex, age, and ethnicity. My research goal is to examine viral, immunologic, and genetic factors in adult glioma risk and patient outcome. The specific aims are: 1. To assess markers of individual variation to HCMV infection and immune function in glioma cases and controls. This will add important molecular data to the existing genetic and epidemiologic data on infection and immune function from the parent grant. This is important in validating the self-reported epidemiologic data. 2. To perform a case-control analysis of glioma risk utilizing epidemiologic and genetic data and markers of infection and immune function. I will employ the methods of multiple logistic regression to model glioma risk as a function of genetic, molecular, and epidemiologic variables. I will incorporate gene-environment and gene-gene interactions as appropriate given the sample size available. 3. To Determine if markers of infection and immune response are associated with clinical outcome and overall survival in glioma patients. I will employ Cox proportional hazards regression to model factors associated with treatment outcome and overall patient survival.